ArticleBioinformatics (Oxford, England)2023
DrTransformer: heuristic cotranscriptional RNA folding using the nearest neighbor energy model.
Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 11 citations in OpenAlex.
- Identification of conserved RNA regulatory switches in living cells using RNA secondary structure ensemble mapping and covariation analysis.Nature biotechnology · 2026Article
- StraD: a coarse-grained simulation of co-transcriptional RNA folding.NAR genomics and bioinformatics · 2025Article
- Rapid folding of nascent RNA regulates eukaryotic RNA biogenesis.Molecular cell · 2025Article
- Computational modeling of cotranscriptional RNA folding.Computational and structural biotechnology journal · 2025Review
- Tree polynomials identify a link between co-transcriptional R-loops and nascent RNA folding.PLoS computational biology · 2024Article
- Genome-wide probing of eukaryotic nascent RNA structure elucidates cotranscriptional folding and its antimutagenic effect.Nature communications · 2023Article
- DrForna: visualization of cotranscriptional folding.Bioinformatics (Oxford, England) · 2023Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
Abstract
motivationFolding during transcription can have an important influence on the structure and function of RNA molecules, as regions closer to the 5' end can fold into metastable structures before potentially stronger interactions with the 3' end become available. Thermodynamic RNA folding models are not suitable to predict structures that result from cotranscriptional folding, as they can only calculate properties of the equilibrium distribution. Other software packages that simulate the kinetic process of RNA folding during transcription exist, but they are mostly applicable for short sequences.
resultsWe present a new algorithm that tracks changes to the RNA secondary structure ensemble during transcription. At every transcription step, new representative local minima are identified, a neighborhood relation is defined and transition rates are estimated for kinetic simulations. After every simulation, a part of the ensemble is removed and the remainder is used to search for new representative structures. The presented algorithm is deterministic (up to numeric instabilities of simulations), fast (in comparison with existing methods), and it is capable of folding RNAs much longer than 200 nucleotides. AVAILABILITY AND IMPLEMENTATION: This software is open-source and available at https://github.com/ViennaRNA/drtransformer. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.